Sidharth Baskaran
About Sidharth Baskaran
Sidharth Baskaran is a Founding Engineer at Automorphic, where he focuses on developing effective learning strategies for language models. He studied Computer Science at Georgia Institute of Technology and has held research positions at various institutions, including Georgia Tech and Oak Ridge National Laboratory.
Work at Automorphic
Sidharth Baskaran serves as a Founding Engineer at Automorphic, a position he has held since 2023. In this role, he focuses on developing effective continual learning strategies for language models. His work involves creating methods to inject domain knowledge into these models, enhancing their performance and applicability in various contexts. Automorphic operates out of San Francisco, California, where Baskaran contributes to the company's innovative approach to artificial intelligence.
Education and Expertise
Sidharth Baskaran is currently pursuing a Bachelor of Science in Computer Science at the Georgia Institute of Technology, a program he began in 2022. He previously completed his education at the Liberal Arts & Science Academy, where he studied from 2018 to 2022. His academic background provides a strong foundation for his work in technology and research, particularly in the field of language models and machine learning.
Background
Before joining Automorphic, Sidharth Baskaran gained valuable experience as an Undergraduate Researcher at the Georgia Institute of Technology's Fung Lab from 2022 to 2023. He also completed research internships at the Oak Ridge National Laboratory in 2023 and at The University of Texas at Austin in 2021. These roles allowed him to develop practical skills and insights into research methodologies and applications in computer science.
Research Experience
Sidharth Baskaran's research experience includes significant roles at various prestigious institutions. At the Georgia Institute of Technology, he worked in the Fung Lab for ten months, contributing to ongoing research projects. His internship at Oak Ridge National Laboratory lasted one month and was conducted remotely, while his earlier internship at The University of Texas at Austin spanned five months. These experiences have equipped him with a diverse skill set in research and development.